{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": [],
      "gpuType": "T4"
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "source": [
        "# Integrate txtai with Postgres\n",
        "\n",
        "[txtai](https://github.com/neuml/txtai) is an all-in-one embeddings database for semantic search, LLM orchestration and language model workflows.\n",
        "\n",
        "The default persistence methods for txtai are local and file-based. `SQLite` for content, `Faiss` for vectors and `NetworkX` for graph data. The main value add of txtai is getting up and running quickly with a minimal amount of external dependencies.\n",
        "\n",
        "Another key feature of txtai is being able to quickly move from prototyping to production. This notebook will demonstrate how txtai can integrate with [Postgres](https://www.postgresql.org/), a powerful, production-ready and open source object-relational database system. After txtai persists content to Postgres, we'll show it can be directly queried with SQL from any Postgres client 🔥"
      ],
      "metadata": {
        "id": "j7jcAie81QIH"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Install dependencies\n",
        "\n",
        "Install `txtai` and all dependencies."
      ],
      "metadata": {
        "id": "wB0wcLc32IJZ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "%%capture\n",
        "\n",
        "# Install txtai and dependencies\n",
        "!pip install git+https://github.com/neuml/txtai#egg=txtai[ann,database,graph]"
      ],
      "metadata": {
        "id": "ITs6ttB5gU48"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Install Postgres\n",
        "\n",
        "Next, we'll install Postgres and start a Postgres instance. This will also install the `pgvector` extension to enable vector search and storage.\n",
        "\n",
        "*Note: With local environments, consider running Postgres as a Docker container.*"
      ],
      "metadata": {
        "id": "VMsobwvU2QUh"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "%%capture\n",
        "\n",
        "# Install Postgres and pgvector\n",
        "!apt-get update && apt install postgresql postgresql-server-dev-14\n",
        "!git clone --branch v0.6.2 https://github.com/pgvector/pgvector.git\n",
        "!cd pgvector && make && make install\n",
        "\n",
        "# Start database\n",
        "!service postgresql start\n",
        "!sudo -u postgres psql -U postgres -c \"ALTER USER postgres PASSWORD 'pass';\""
      ],
      "metadata": {
        "id": "S0P8hEBL2OYd"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Build an Embeddings database\n",
        "First, we'll load the 100K most popular articles from Wikipedia. This example will store vectors and content in Postgres."
      ],
      "metadata": {
        "id": "sYrfpy5D2j4Y"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from txtai import Embeddings\n",
        "\n",
        "# URL set in code for demo purposes. Use environment variables in production.\n",
        "url = \"postgresql+psycopg2://postgres:pass@localhost/postgres\"\n",
        "\n",
        "# Create embeddings\n",
        "embeddings = Embeddings(\n",
        "    content=url,\n",
        "    backend=\"pgvector\",\n",
        "    pgvector={\n",
        "        \"url\": url\n",
        "    }\n",
        ")\n",
        "\n",
        "# Load dataset\n",
        "wikipedia = Embeddings()\n",
        "wikipedia.load(provider=\"huggingface-hub\", container=\"neuml/txtai-wikipedia\")\n",
        "\n",
        "query = \"\"\"\n",
        "SELECT id, text FROM txtai\n",
        "order by percentile desc\n",
        "LIMIT 100000\n",
        "\"\"\"\n",
        "\n",
        "# Index dataset\n",
        "embeddings.index(wikipedia.search(query))"
      ],
      "metadata": {
        "id": "a3qM3T5uj007"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "embeddings.search(\"Tell me about a mythical horse\", 1)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "yfjbASug005C",
        "outputId": "336b27f6-ae68-4270-ef11-bb6578600abf"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[{'id': 'Unicorn',\n",
              "  'text': 'The unicorn is a legendary creature that has been described since antiquity as a beast with a single large, pointed, spiraling horn projecting from its forehead.',\n",
              "  'score': 0.6493861675262451}]"
            ]
          },
          "metadata": {},
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "embeddings.search(\"What is the main ingredient in Ketchup?\", 1)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "L0TP2y5c08tv",
        "outputId": "4b6c2eb7-285e-4a19-fa11-2e2aae4ab5ea"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[{'id': 'Ketchup',\n",
              "  'text': 'Ketchup or catsup is a table condiment with a sweet and sour flavor. The unmodified term (\"ketchup\") now typically refers to tomato ketchup, although early recipes for various different varieties of ketchup contained mushrooms, oysters, mussels, egg whites, grapes or walnuts, among other ingredients. ',\n",
              "  'score': 0.6998806595802307}]"
            ]
          },
          "metadata": {},
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Now, let's explore how the data is stored in further detail. We'll save the database and take a look."
      ],
      "metadata": {
        "id": "LNLXmOTV2z32"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "%env TOKENIZERS_PARALLELISM=false\n",
        "\n",
        "# Commit results to the database\n",
        "embeddings.save(\"test\")\n",
        "embeddings.close()\n",
        "\n",
        "!ls test\n",
        "!cat test/config.json"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "-4v7joOC23HY",
        "outputId": "73ef3537-42c7-4c43-be0c-c4ecdbe2c0bd"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "env: TOKENIZERS_PARALLELISM=false\n",
            "config.json\n",
            "{\n",
            "  \"content\": \"postgresql+psycopg2://postgres:pass@localhost/postgres\",\n",
            "  \"backend\": \"pgvector\",\n",
            "  \"pgvector\": {\n",
            "    \"url\": \"postgresql+psycopg2://postgres:pass@localhost/postgres\"\n",
            "  },\n",
            "  \"path\": \"sentence-transformers/all-MiniLM-L6-v2\",\n",
            "  \"dimensions\": 384,\n",
            "  \"offset\": 100000\n",
            "}"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Note how there is only a configuration file with the database details. Let's explore the Postgres database.\n"
      ],
      "metadata": {
        "id": "6g-FZJDT2-J6"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!PGPASSWORD=pass psql -h localhost -U postgres -c \"SELECT * from sections order by indexid LIMIT 1\"\n",
        "!PGPASSWORD=pass psql -h localhost -U postgres -c \"SELECT * from vectors order by indexid LIMIT 1\""
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "XLfvxYoU3NDS",
        "outputId": "4180c5a5-d52a-4acc-9269-9f90bee2d865"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            " indexid |    id     |                    text                     | tags |           entry            \n",
            "---------+-----------+---------------------------------------------+------+----------------------------\n",
            "       0 | Main Page | Welcome to Wikipedia,                      +|      | 2024-04-24 17:02:55.335643\n",
            "         |           | the free encyclopedia that anyone can edit.+|      | \n",
            "         |           |  articles in English                        |      | \n",
            "(1 row)\n",
            "\n",
            " indexid |                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                    embedding                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                    \n",
            "---------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\n",
            "       0 | [0.006224656,0.010993197,-0.020153109,0.046154346,-0.0067520724,0.011807963,-0.014358369,0.028947443,-0.01586261,0.09301224,0.055368096,0.040113293,0.01760968,0.013503182,-0.016870098,-0.012503422,-0.008597899,0.026588641,-0.08471918,-0.04503593,0.060253955,-0.0031328013,0.11977076,0.024629632,-0.022491025,-0.03793595,0.0061959964,0.0072981887,0.00796152,-0.027184578,-0.10998758,0.07487334,0.08721705,-0.003783297,2.4116285e-05,0.01077903,0.009361188,0.020106519,0.025032397,0.026869925,-0.0111307595,-0.09997612,0.019141614,0.015201731,-0.000267303,0.12866877,-0.04923438,-0.059046485,0.013421367,0.04622524,-0.024259627,-0.01578652,-0.057170264,-0.058802612,0.055165343,-0.016757669,-0.11283095,-0.010731938,-0.03237114,-0.09259695,0.026988069,0.044143338,-0.062587716,0.12294508,0.017795669,-0.0022635453,-0.000859233,0.083078146,0.009367941,-0.08944039,0.020436421,0.03098923,0.08612748,0.06908283,-0.011492079,-0.057584476,0.007815615,0.07544962,-0.07507969,-0.031771705,0.06140103,0.045389958,0.0010914068,-0.014727611,-0.0048347805,-0.008656534,-0.011555558,-0.027875263,0.044627354,-0.041978024,0.0023647482,-0.068146914,0.10593634,0.00459672,-0.0043201237,-0.003424118,0.03128756,-0.031586997,0.006560516,0.047244154,0.06694147,-0.0024762554,-0.034794953,0.0685723,-0.115641095,-0.07013151,-0.029626537,0.05652201,-0.0047345776,-0.08600411,-0.02712477,0.06307427,-0.020134196,-0.05487676,-0.010889723,-0.012801617,0.0070655714,0.01565348,0.06468041,-0.0027397969,-0.052258722,0.025590474,0.0004874447,0.0567211,-0.01091167,-0.016167942,-0.056139555,-3.360483e-33,0.06776523,0.07398922,0.021548307,0.0522404,-0.063432045,0.009229409,-0.09691417,-0.05641955,-0.055137824,-0.04107145,0.055179913,0.06995813,-0.043880165,-0.060650233,0.0026008217,0.026983975,-0.03595947,0.11371047,0.018100752,0.027147746,0.034160867,0.050208986,-0.03631904,-0.0035121094,-0.06707664,0.0063270847,0.008653185,-0.11846966,0.0075610424,0.0021807787,0.015405556,-0.017979044,-0.04683855,-0.015657036,-0.04022284,-0.017653259,0.036167417,-0.042651214,0.005417714,-0.09401236,-0.032427326,-0.017289782,-0.04060469,0.015479944,-0.011029847,0.0719449,0.0051068533,-0.06828172,0.08947456,-0.04907346,0.016336497,0.032021444,-0.04396127,-0.0036975099,0.05712386,0.089574024,0.070081435,0.06301272,0.0010954054,0.01729774,0.047785297,0.09727387,-0.0016659853,0.01636651,-0.011960934,0.08042555,-0.044158004,0.015542993,0.039673716,-0.023705207,-0.0705359,-0.0060911574,0.00903571,0.056801423,-0.04288321,0.075399615,-0.060097944,-0.070493154,-0.039201744,0.02091038,0.021842068,-0.05289644,0.032512337,-0.04969522,0.014612853,0.03174613,0.019972498,-0.018262003,0.10062693,0.03011935,0.058835424,0.008656911,-0.0693178,-0.0003107625,-0.035816267,8.551262e-34,-0.08153472,-0.109941624,0.0010887359,0.058030974,-0.05916192,-0.017850945,-0.11167397,0.107069634,0.041289993,-0.019890498,-0.0026840265,-0.098246865,-0.052144755,0.06551777,-0.04089334,-0.028716525,0.03241684,-0.06699939,-0.09264921,0.124276765,-0.07738617,-0.008159692,-0.04621176,-0.003925314,-0.028218271,0.004362621,0.0662335,0.05448178,-0.049431797,0.001068466,-0.06137263,-0.07963246,-0.056226213,-0.050934546,-0.08301799,-0.03711833,0.001591565,-0.042424005,-0.020324506,-0.05731789,0.043870095,0.040546007,0.008878352,-0.06366917,-0.030763976,-0.028072147,-0.101492785,0.0049343915,0.008031439,-0.029323548,0.052847456,-0.015137294,0.02956745,-0.10447449,0.035620738,0.0025644598,-0.032033995,-0.075608805,0.060582157,-0.03741465,-0.05037591,0.024472151,-0.19789998,0.14253329,0.027650978,0.025539117,-0.09750419,0.07298771,0.017285004,-0.05192262,0.022350593,-0.033429917,0.034556758,-0.06539779,0.03567383,-0.023474114,0.04871094,0.0045313137,0.024971936,-0.09835969,-0.0012533984,-0.0019569201,0.015049834,0.009462184,0.026953677,0.045278806,0.024228122,0.0009281798,-0.023020085,-0.024668744,0.012790688,-0.021721361,-0.026636621,0.06193553,-0.026421277,-2.0252372e-08,-0.009053995,-0.022655917,-0.05537436,0.09484807,0.006692196,-0.05305789,0.019044574,0.050973132,-0.004839857,0.07959955,-0.0562942,0.043415457,-0.051326852,0.04842562,-0.022588398,0.05024676,0.022963611,0.0699145,0.016860556,0.009093765,0.04256753,0.016887672,0.04927324,-0.0092127,0.013626016,0.045127258,-0.005615936,-0.039890807,0.0928744,-0.10173735,-0.11896241,-0.0064999964,-0.04553107,0.04174175,0.030028146,0.042279907,0.000696869,0.0012388963,-0.02783201,-0.048495434,0.04485023,0.009498387,-0.009533283,0.036473263,0.028421838,0.01844087,0.01952972,-0.021264598,0.08634994,-0.022555202,0.060081147,0.013670229,0.1497612,-0.021247797,-0.008887135,0.0306203,-0.007087516,0.024898361,0.05220465,0.012215928,0.02570937,0.046506412,0.08931996,-0.0010894431]\n",
            "(1 row)\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Note how the text content and vectors are stored in this Postgres instance."
      ],
      "metadata": {
        "id": "slEWXtIz3NqN"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Graph Embeddings\n",
        "\n",
        "Next, we'll rebuild the same embeddings database and enable a graph component. This graph component will also persist content to Postgres."
      ],
      "metadata": {
        "id": "fSjuwiQw3UcH"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from txtai import Embeddings\n",
        "\n",
        "# Create embeddings\n",
        "embeddings = Embeddings(\n",
        "    content=url,\n",
        "    backend=\"pgvector\",\n",
        "    pgvector={\n",
        "        \"url\": url\n",
        "    },\n",
        "    graph={\n",
        "        \"backend\": \"rdbms\",\n",
        "        \"url\": url,\n",
        "        \"approximate\": False,\n",
        "    }\n",
        ")\n",
        "\n",
        "# Index dataset\n",
        "embeddings.index(wikipedia.search(query))"
      ],
      "metadata": {
        "id": "DDj_39ak0_fF"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "Now, as with prior graph examples, let's build a new graph with a query. Then we'll plot that subgraph."
      ],
      "metadata": {
        "id": "HG_cABE03e1P"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "g = embeddings.graph.search(\"\"\"\n",
        "MATCH P=({id: \"Roman Empire\"})-[*1..3]->({id: \"Saxons\"})-[*1..3]->({id: \"Vikings\"})-[*1..3]->({id: \"Battle of Hastings\"})\n",
        "RETURN P\n",
        "LIMIT 20\n",
        "\"\"\", graph=True)"
      ],
      "metadata": {
        "id": "Yhf6nkyb1ChP"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt\n",
        "import networkx as nx\n",
        "\n",
        "def plot(graph):\n",
        "    labels = {x: f\"{graph.attribute(x, 'id')}\" for x in graph.scan()}\n",
        "    colors = [\"#D32F2F\", \"#0277bd\", \"#7e57c2\", \"#757575\"]\n",
        "\n",
        "    results = embeddings.batchsimilarity(labels.values(), [\"Roman Empire\", \"Germanic Barbarians\", \"Viking conquest and siege\", \"Norman Conquest of England\"])\n",
        "    colors = [colors[x[0][0]] for x in results]\n",
        "\n",
        "    options = {\n",
        "        \"node_size\": 2000,\n",
        "        \"node_color\": colors,\n",
        "        \"edge_color\": \"#454545\",\n",
        "        \"font_color\": \"#efefef\",\n",
        "        \"font_size\": 11,\n",
        "        \"alpha\": 1.0,\n",
        "    }\n",
        "\n",
        "    fig, ax = plt.subplots(figsize=(20, 9))\n",
        "    pos = nx.spring_layout(graph.backend, seed=512, k=0.9, iterations=50)\n",
        "    nx.draw_networkx(graph.backend, pos=pos, labels=labels, **options)\n",
        "    ax.set_facecolor(\"#303030\")\n",
        "    ax.axis(\"off\")\n",
        "    fig.set_facecolor(\"#303030\")\n",
        "\n",
        "    plt.show()\n",
        "\n",
        "plot(g)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 730
        },
        "id": "mN6O8b491Exm",
        "outputId": "4a7276ef-fdb5-4b31-da35-86c27665549d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 2000x900 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "🚀 Very exciting. A full graph embeddings database all backed by Postgres!\n",
        "\n",
        "Let's explore the database once again."
      ],
      "metadata": {
        "id": "AVjFXwlo3rzI"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "embeddings.save(\"test\")"
      ],
      "metadata": {
        "id": "Exx4xHvL1G_y"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "!PGPASSWORD=pass psql -h localhost -U postgres -c \"SELECT * from sections order by indexid LIMIT 1\"\n",
        "!PGPASSWORD=pass psql -h localhost -U postgres -c \"SELECT * from vectors order by indexid LIMIT 1\"\n",
        "!PGPASSWORD=pass psql -h localhost -U postgres -c \"SELECT * from nodes LIMIT 1\"\n",
        "!PGPASSWORD=pass psql -h localhost -U postgres -c \"SELECT * from edges LIMIT 1\""
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "CGqlh84o1Ku7",
        "outputId": "37fee7e6-1e7b-42e9-c803-2bebc7186633"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            " indexid |    id     |                    text                     | tags |           entry            \n",
            "---------+-----------+---------------------------------------------+------+----------------------------\n",
            "       0 | Main Page | Welcome to Wikipedia,                      +|      | 2024-04-24 17:24:04.402629\n",
            "         |           | the free encyclopedia that anyone can edit.+|      | \n",
            "         |           |  articles in English                        |      | \n",
            "(1 row)\n",
            "\n",
            " indexid |                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                    embedding                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                    \n",
            "---------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\n",
            "       0 | [0.006224656,0.010993197,-0.020153109,0.046154346,-0.0067520724,0.011807963,-0.014358369,0.028947443,-0.01586261,0.09301224,0.055368096,0.040113293,0.01760968,0.013503182,-0.016870098,-0.012503422,-0.008597899,0.026588641,-0.08471918,-0.04503593,0.060253955,-0.0031328013,0.11977076,0.024629632,-0.022491025,-0.03793595,0.0061959964,0.0072981887,0.00796152,-0.027184578,-0.10998758,0.07487334,0.08721705,-0.003783297,2.4116285e-05,0.01077903,0.009361188,0.020106519,0.025032397,0.026869925,-0.0111307595,-0.09997612,0.019141614,0.015201731,-0.000267303,0.12866877,-0.04923438,-0.059046485,0.013421367,0.04622524,-0.024259627,-0.01578652,-0.057170264,-0.058802612,0.055165343,-0.016757669,-0.11283095,-0.010731938,-0.03237114,-0.09259695,0.026988069,0.044143338,-0.062587716,0.12294508,0.017795669,-0.0022635453,-0.000859233,0.083078146,0.009367941,-0.08944039,0.020436421,0.03098923,0.08612748,0.06908283,-0.011492079,-0.057584476,0.007815615,0.07544962,-0.07507969,-0.031771705,0.06140103,0.045389958,0.0010914068,-0.014727611,-0.0048347805,-0.008656534,-0.011555558,-0.027875263,0.044627354,-0.041978024,0.0023647482,-0.068146914,0.10593634,0.00459672,-0.0043201237,-0.003424118,0.03128756,-0.031586997,0.006560516,0.047244154,0.06694147,-0.0024762554,-0.034794953,0.0685723,-0.115641095,-0.07013151,-0.029626537,0.05652201,-0.0047345776,-0.08600411,-0.02712477,0.06307427,-0.020134196,-0.05487676,-0.010889723,-0.012801617,0.0070655714,0.01565348,0.06468041,-0.0027397969,-0.052258722,0.025590474,0.0004874447,0.0567211,-0.01091167,-0.016167942,-0.056139555,-3.360483e-33,0.06776523,0.07398922,0.021548307,0.0522404,-0.063432045,0.009229409,-0.09691417,-0.05641955,-0.055137824,-0.04107145,0.055179913,0.06995813,-0.043880165,-0.060650233,0.0026008217,0.026983975,-0.03595947,0.11371047,0.018100752,0.027147746,0.034160867,0.050208986,-0.03631904,-0.0035121094,-0.06707664,0.0063270847,0.008653185,-0.11846966,0.0075610424,0.0021807787,0.015405556,-0.017979044,-0.04683855,-0.015657036,-0.04022284,-0.017653259,0.036167417,-0.042651214,0.005417714,-0.09401236,-0.032427326,-0.017289782,-0.04060469,0.015479944,-0.011029847,0.0719449,0.0051068533,-0.06828172,0.08947456,-0.04907346,0.016336497,0.032021444,-0.04396127,-0.0036975099,0.05712386,0.089574024,0.070081435,0.06301272,0.0010954054,0.01729774,0.047785297,0.09727387,-0.0016659853,0.01636651,-0.011960934,0.08042555,-0.044158004,0.015542993,0.039673716,-0.023705207,-0.0705359,-0.0060911574,0.00903571,0.056801423,-0.04288321,0.075399615,-0.060097944,-0.070493154,-0.039201744,0.02091038,0.021842068,-0.05289644,0.032512337,-0.04969522,0.014612853,0.03174613,0.019972498,-0.018262003,0.10062693,0.03011935,0.058835424,0.008656911,-0.0693178,-0.0003107625,-0.035816267,8.551262e-34,-0.08153472,-0.109941624,0.0010887359,0.058030974,-0.05916192,-0.017850945,-0.11167397,0.107069634,0.041289993,-0.019890498,-0.0026840265,-0.098246865,-0.052144755,0.06551777,-0.04089334,-0.028716525,0.03241684,-0.06699939,-0.09264921,0.124276765,-0.07738617,-0.008159692,-0.04621176,-0.003925314,-0.028218271,0.004362621,0.0662335,0.05448178,-0.049431797,0.001068466,-0.06137263,-0.07963246,-0.056226213,-0.050934546,-0.08301799,-0.03711833,0.001591565,-0.042424005,-0.020324506,-0.05731789,0.043870095,0.040546007,0.008878352,-0.06366917,-0.030763976,-0.028072147,-0.101492785,0.0049343915,0.008031439,-0.029323548,0.052847456,-0.015137294,0.02956745,-0.10447449,0.035620738,0.0025644598,-0.032033995,-0.075608805,0.060582157,-0.03741465,-0.05037591,0.024472151,-0.19789998,0.14253329,0.027650978,0.025539117,-0.09750419,0.07298771,0.017285004,-0.05192262,0.022350593,-0.033429917,0.034556758,-0.06539779,0.03567383,-0.023474114,0.04871094,0.0045313137,0.024971936,-0.09835969,-0.0012533984,-0.0019569201,0.015049834,0.009462184,0.026953677,0.045278806,0.024228122,0.0009281798,-0.023020085,-0.024668744,0.012790688,-0.021721361,-0.026636621,0.06193553,-0.026421277,-2.0252372e-08,-0.009053995,-0.022655917,-0.05537436,0.09484807,0.006692196,-0.05305789,0.019044574,0.050973132,-0.004839857,0.07959955,-0.0562942,0.043415457,-0.051326852,0.04842562,-0.022588398,0.05024676,0.022963611,0.0699145,0.016860556,0.009093765,0.04256753,0.016887672,0.04927324,-0.0092127,0.013626016,0.045127258,-0.005615936,-0.039890807,0.0928744,-0.10173735,-0.11896241,-0.0064999964,-0.04553107,0.04174175,0.030028146,0.042279907,0.000696869,0.0012388963,-0.02783201,-0.048495434,0.04485023,0.009498387,-0.009533283,0.036473263,0.028421838,0.01844087,0.01952972,-0.021264598,0.08634994,-0.022555202,0.060081147,0.013670229,0.1497612,-0.021247797,-0.008887135,0.0306203,-0.007087516,0.024898361,0.05220465,0.012215928,0.02570937,0.046506412,0.08931996,-0.0010894431]\n",
            "(1 row)\n",
            "\n",
            " ID |                                                        _metadata                                                        \n",
            "----+-------------------------------------------------------------------------------------------------------------------------\n",
            " 0  | {\"id\": \"Main Page\", \"data\": \"Welcome to Wikipedia,\\nthe free encyclopedia that anyone can edit.\\n articles in English\"}\n",
            "(1 row)\n",
            "\n",
            "    ID    |           _metadata            | Source | Target \n",
            "----------+--------------------------------+--------+--------\n",
            " __0__179 | {\"weight\": 0.7411725521087646} | 0      | 179\n",
            "(1 row)\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "As we saw before, text content and vectors are stored in the database. Additionally, we now have graph node and edge data.\n",
        "\n",
        "Let's take this up a level."
      ],
      "metadata": {
        "id": "5aLMn_RS316T"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Vector search with Postgres\n",
        "\n",
        "Now that the data is persisted in Postgres, can we run vector search without loading the txtai database locally? Yes!"
      ],
      "metadata": {
        "id": "4o9TVWG53_9W"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Query with a search string\n",
        "query = str(list(embeddings.transform(\"Roman Empire\")))\n",
        "query = f\"\"\"\n",
        "SELECT id, (embedding <#> '{query}') * -1 AS score, text FROM sections s \\\n",
        "JOIN vectors v ON s.indexid = v.indexid \\\n",
        "ORDER by score desc LIMIT 5\n",
        "\"\"\"\n",
        "\n",
        "!PGPASSWORD=pass psql -h localhost -U postgres -c \"{query}\""
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "jOgh1MBO1MvW",
        "outputId": "235e1a80-3fc2-457a-861d-f8791febc46d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "             id              |       score        |                                                                                                                                                                                                                                                                                                            text                                                                                                                                                                                                                                                                                                            \n",
            "-----------------------------+--------------------+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\n",
            " Roman Empire                | 0.6798915266990662 | The Roman Empire was the post-Republican state of ancient Rome and is generally understood to mean the period and territory ruled by the Romans following Octavian's assumption of sole rule under the Principate in 31 BC. It included territory in Europe, North Africa, and Western Asia, and was ruled by emperors. The fall of the Western Roman Empire in 476 conventionally marks the end of classical antiquity and the beginning of the Middle Ages.\n",
            " History of the Roman Empire | 0.6295346617698669 | The history of the Roman Empire covers the history of ancient Rome from the fall of the Roman Republic in 27 BC until the abdication of Romulus Augustulus in AD 476 in the West, and the Fall of Constantinople in the East in AD 1453. Ancient Rome became a territorial empire while still a republic, but was then ruled by Roman emperors beginning with Augustus, becoming the Roman Empire following the death of the last republican dictator, the first emperor's adoptive father Julius Caesar.\n",
            " Roman Republic              | 0.6280723810195923 | The Roman Republic was the era of classical Roman civilization beginning with the overthrow of the Roman Kingdom (traditionally dated to 509 BC) and ending in 27 BC with the establishment of the Roman Empire. During this period, Rome's control expanded from the city's immediate surroundings to hegemony over the entire Mediterranean world.\n",
            " Latin Empire                |  0.613895058631897 | The Latin Empire, also referred to as the Latin Empire of Constantinople, was a feudal Crusader state founded by the leaders of the Fourth Crusade on lands captured from the Byzantine Empire. The Latin Empire was intended to replace the Byzantine Empire as the Western-recognized Roman Empire in the east, with a Catholic emperor enthroned in place of the Eastern Orthodox Roman emperors. The main objective of the Latin Empire was planned by Venice, which promoted the creation of this state for their self-benefit.\n",
            " Augustus                    | 0.6021512150764465 | Gaius Julius Caesar Augustus (born Gaius Octavius; 23 September 63 BC – 19 August AD 14), also known as Octavianus or Octavian, was the founder of the Roman Empire; he reigned as the first Roman emperor from 27 BC until his death in AD 14. The reign of Augustus initiated an imperial cult as well as an era associated with imperial peace, the Pax Romana or Pax Augusta, in which the Roman world was largely free of armed conflict aside from expansionary wars and the Year of the Four Emperors. The Principate system of imperial rule established by Augustus lasted until the Crisis of the Third Century.\n",
            "(5 rows)\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Just like that, vector search without a local txtai instance! The only part needed is a way to vectorize the search query. This can easily be replaced with an API vectorization service.\n",
        "\n",
        "We can also find the most similar rows for an existing row."
      ],
      "metadata": {
        "id": "CM2sr_NI4Mo5"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Find top n results closest to an existing row\n",
        "query = \"\"\"\n",
        "SELECT id, text FROM sections s \\\n",
        "JOIN vectors v ON s.indexid = v.indexid \\\n",
        "WHERE v.indexid != 738 ORDER by v.embedding <#> (SELECT embedding FROM vectors WHERE indexid=738) LIMIT 5\n",
        "\"\"\"\n",
        "\n",
        "!PGPASSWORD=pass psql -h localhost -U postgres -c \"{query}\""
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "MnolJkL31OzU",
        "outputId": "d23954b0-849e-45b8-f32e-6af835e2a18f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "                id                |                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                       text                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                        \n",
            "----------------------------------+-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\n",
            " History of the Roman Empire      | The history of the Roman Empire covers the history of ancient Rome from the fall of the Roman Republic in 27 BC until the abdication of Romulus Augustulus in AD 476 in the West, and the Fall of Constantinople in the East in AD 1453. Ancient Rome became a territorial empire while still a republic, but was then ruled by Roman emperors beginning with Augustus, becoming the Roman Empire following the death of the last republican dictator, the first emperor's adoptive father Julius Caesar.\n",
            " Roman Republic                   | The Roman Republic was the era of classical Roman civilization beginning with the overthrow of the Roman Kingdom (traditionally dated to 509 BC) and ending in 27 BC with the establishment of the Roman Empire. During this period, Rome's control expanded from the city's immediate surroundings to hegemony over the entire Mediterranean world.\n",
            " Roman Kingdom                    | The Roman Kingdom, also referred to as the Roman monarchy or the regal period of ancient Rome, was the earliest period of Roman history when the city and its territory were ruled by kings. According to tradition, the Roman Kingdom began with the city's founding  753 BC, with settlements around the Palatine Hill along the river Tiber in central Italy, and ended with the overthrow of the kings and the establishment of the Republic  509 BC.\n",
            " Byzantine Empire                 | The Byzantine Empire, also referred to as the Eastern Roman Empire, was the continuation of the Roman Empire centered in Constantinople during Late Antiquity and the Middle Ages. The eastern half of the Empire survived the conditions that caused the fall of the West in the 5th century AD, and continued to exist until the fall of Constantinople to the Ottoman Empire in 1453. During most of its existence, the empire remained the most powerful economic, cultural, and military force in the Mediterranean world. The term \"Byzantine Empire\" was only coined following the empire's demise: its citizens referred to the polity as the \"Roman Empire\" and to themselves as \"Romans\". Due to the imperial seat's move from Rome to Byzantium, the adoption of state Christianity, and the predominance of Greek instead of Latin, modern historians continue to make a distinction between the earlier \"Roman Empire\" and the later \"Byzantine Empire\".\n",
            " Fall of the Western Roman Empire | The fall of the Western Roman Empire, also called the fall of the Roman Empire or the fall of Rome, was the loss of central political control in the Western Roman Empire, a process in which the Empire failed to enforce its rule, and its vast territory was divided into several successor polities. The Roman Empire lost the strengths that had allowed it to exercise effective control over its Western provinces; modern historians posit factors including the effectiveness and numbers of the army, the health and numbers of the Roman population, the strength of the economy, the competence of the emperors, the internal struggles for power, the religious changes of the period, and the efficiency of the civil administration. Increasing pressure from invading barbarians outside Roman culture also contributed greatly to the collapse. Climatic changes and both endemic and epidemic disease drove many of these immediate factors. The reasons for the collapse are major subjects of the historiography of the ancient world and they inform much modern discourse on state failure.\n",
            "(5 rows)\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Wrapping up\n",
        "\n",
        "From prototyping to production, txtai is ready for all that can be thrown it's way. As always, this functionality is just the beginning and will continue to improve over time. But this is a big deal and has impacts for future services such as [txtai.cloud](https://txtai.cloud) ☁️\n",
        "\n",
        "Stay tuned!\n"
      ],
      "metadata": {
        "id": "o7uQBS0N4nvN"
      }
    }
  ]
}